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Ethical Guidelines for Statistical Practice
American Statistical Association Prepared by the Committee on Professional
Ethics
Approved by the Board of Directors, August 7, 1999
Executive Summary
This document contains two parts: I. Preamble and II. Ethical Guidelines.
The Preamble addresses
A. Purpose of the Guidelines,
B. Statistics and Society, and
C. Shared Values.
The purpose of the document is to encourage ethical and effective statistical
work in morally conducive working environments. It is also intended to
assist students in learning to perform statistical work responsibly. Statistics
plays a vital role in many aspects of science, the economy, governance,
and even entertainment. It is important that all statistical practitioners
recognize their potential impact on the broader society and the attendant
ethical obligations to perform their work responsibly. Furthermore, practitioners
are encouraged to exercise "good professional citizenship" in order to
improve the public climate for, understanding of, and respect for the
use of statistics throughout its range of applications.
The Ethical Guidelines address eight general topic areas
and specify important ethical considerations under each topic. A. Professionalism
points out the need for competence, judgment, diligence, self-respect,
and worthiness of the respect of other people. B. Responsibilities to
Funders, Clients, and Employers discusses the practitioner's responsibility
for assuring that statistical work is suitable to the needs and resources
of those who are paying for it, that funders understand the capabilities
and limitations of statistics in addressing their problem, and that the
funder's confidential information is protected. C. Responsibilities in
Publications and Testimony addresses the need to report sufficient information
to give readers, including other practitioners, a clear understanding
of the intent of the work, how and by whom it was performed, and any limitations
on its validity. D. Responsibilities to Research Subjects describes requirements
for protecting the interests of human and animal subjects of research
-- not only during data collection but also in the analysis, interpretation,
and publication of the resulting findings. E. Responsibilities to Research
Team Colleagues addresses the mutual responsibilities of professionals
participating in multidisciplinary research teams. F. Responsibilities
to Other Statisticians or Statistical Practitioners notes the interdependence
of professionals doing similar work, whether in the same or different
organizations. Basically, they must contribute to the strength of their
professions overall, by sharing non-proprietary data and methods, by participating
in peer review, and by respecting differing professional opinions. G.
Responsibilities Regarding Allegations of Misconduct addresses the sometimes
painful process of investigating potential ethical violations and treating
those involved with both justice and respect. Finally, H. Responsibilities
of Employers, Including Organizations, Individuals, Attorneys, or Other
Clients Employing Statistical Practitioners encourages employers and clients
to recognize the highly interdependent nature of statistical ethics and
statistical validity. Employers and clients must not pressure practitioners
to produce a particular "result" regardless of its statistical validity.
They must avoid the potential social harm that can result from the dissemination
of false or misleading statistical work.
I. PREAMBLE
A. Purpose of the Guidelines The American Statistical Association's Ethical
Guidelines for Statistical Practice are intended to help statistical practitioners
make and communicate ethical decisions. Clients, employers, researchers,
policy makers, journalists, and the public should be urged to expect that
statistical practice will be conducted in accordance with these guidelines
and to object when it is not. While learning how to apply statistical
theory to problems, students should be encouraged to use these guidelines
whether or not their target professional specialty will be "statistician."
Employers, attorneys, and other clients of statistical practitioners have
a responsibility to provide a moral environment that fosters the use of
these ethical guidelines. Application of these or any other ethical guidelines
generally requires good judgment and common sense. The guidelines may
be partially conflicting in specific cases. The application of these guidelines
in any given case can depend on issues of law and shared values, work-group
politics, the status and power of the individuals involved, and the extent
to which the ethical lapses pose a threat to the public, to one's profession,
or to one's organization. The individuals and institutions responsible
for making such ethical decisions can receive valuable assistance by discussion
and consultation with others, particularly persons with divergent interests
with respect to the ethical issues under consideration.
B. Statistics and Society
The professional performance of statistical analyses is essential to many
aspects of society. The use of statistics in medical diagnoses and biomedical
research may affect whether individuals live or die, whether their health
is protected or jeopardized, and whether medical science advances or gets
sidetracked. Life, death, and health, as well as efficiency, may be at
stake in statistical analyses of occupational, environmental, or transportation
safety. Early detection and control of new or recurrent infectious diseases
depend on sound epidemiological statistics. Mental and social health may
be at stake in psychological and sociological applications of statistical
analysis. Effective functioning of the economy depends on the availability
of reliable, timely, and properly interpreted economic data. The profitability
of individual firms depends in part on their quality control and their
market research, both of which should rely on statistical methods. Agricultural
productivity benefits greatly from statistically sound applications to
research and output reporting. Governmental policy decisions regarding
public health, criminal justice, social equity, education, the environment,
the siting of critical facilities, and other matters depend in part on
sound statistics. Scientific and engineering research in all disciplines
requires the careful design and analysis of experiments and observations.
To the extent that uncertainty and measurement error are involved -- as
they are in most research -- research design, data quality management,
analysis, and interpretation are all crucially dependent on statistical
concepts and methods. Even in theory, much of science and engineering
involves natural variability. Variability, whether great or small, must
be carefully examined both for random error and for possible researcher
bias or wishful thinking. Statistical tools and methods, like many other
technologies, can be employed either for social good or for evil. The
professionalism encouraged by these guidelines is predicated on their
use in socially responsible pursuits by morally responsible societies,
governments, and employers. Where the end purpose of a statistical application
is itself morally reprehensible, statistical professionalism ceases to
have ethical worth.
C. Shared Values
Because society depends on sound statistical practice, all
practitioners of statistics, whatever their training and occupation, have
social obligations to perform their work in a professional, competent,
and ethical manner. This document is directed to those whose primary occupation
is statistics. Still, the principles expressed here should also guide
the statistical work of professionals in all other disciplines that use
statistical methods. All statistical practitioners are obliged to conduct
their professional activities with responsible attention to: The social
value of their work and the consequences of how well or poorly it is performed.
This includes respect for the life, liberty, dignity, and property of
other people. The avoidance of any tendency to slant statistical work
toward predetermined outcomes. (It is acceptable to advocate a position;
it is not acceptable to misapply statistical methods in doing so.) Statistics
as a science. (As in any science, understanding evolves. Statisticians
have a body of established knowledge but also many unresolved issues that
deserve frank discussion.) The maintenance and upgrading of competence
in their work. Adherence to all applicable laws and regulations, as well
as applicable international covenants, while also seeking to change any
of those that are ethically inappropriate. Preservation of data archives
in a manner consistent with responsible protection of the safety and confidentiality
of any human beings and organizations involved. In addition to ethical
obligations, good professional citizenship encourages: Collegiality and
civility with fellow professionals. Support for improved public understanding
of and respect for statistics. Support for sound statistical practice,
especially when it is unfairly criticized. Exposure of dishonest or incompetent
uses of statistics. Service to one's profession as a statistical editor,
reviewer, or association official and service as an active participant
in (formal or informal) ethical review panels.
II. ETHICAL GUIDELINES
A. Professionalism
Strive for practical relevance in statistical analyses.
Typically, each study should be based on a competent understanding of
the subject matter issues, statistical protocols that are clearly defined
for the stage (exploratory, intermediate, or final) of analysis before
looking at those data that will be decisive for that stage, and technical
criteria to justify both the practical relevance of the study and the
amount of data to be used. Guard against the possibility that a predisposition
by investigators or data providers might predetermine the analytic result.
Employ data selection or sampling methods and analytic approaches that
are designed to assure valid analyses in either frequentist or Bayesian
approaches. Remain current in dynamically evolving statistical methodology;
yesterday's preferred methods may be barely acceptable today and totally
obsolete tomorrow. Assure that adequate statistical and subject-matter
expertise are both applied to any planned study. If this criterion is
not met initially, it is important to add the missing expertise before
completing the study design. Use only statistical methodologies suitable
to the data and to obtaining valid results. For example, address the multiple
potentially confounding factors in observational studies, and use due
caution in drawing causal inferences Do not join a research project unless
you can expect to achieve valid results and unless you are confident that
your name will not be associated with the project or resulting publications
without your explicit consent. The fact that a procedure is automated
does not ensure its correctness or appropriateness; it is also necessary
to understand the theory, the data, and the methods used in each statistical
study. This goal is served best when a competent statistical practitioner
is included early in the research design, preferably in the planning stage.
Recognize that any frequentist statistical test has a random chance of
indicating significance when it is not really present. Running multiple
tests on the same data set at the same stage of an analysis increases
the chance of obtaining at least one invalid result. Selecting the one
"significant" result from a multiplicity of parallel tests poses a grave
risk of an incorrect conclusion. Failure to disclose the full extent of
tests and their results in such a case would be highly misleading. Respect
and acknowledge the contributions and the intellectual property of others.
Disclose conflicts of interest, financial and otherwise, and resolve them.
This may sometimes require divestiture of the conflicting personal interest
or recusal or withdrawal from the professional activity. Examples where
conflict of interest may be problematic include grant reviews, other peer
reviews, and tensions between scholarship and personal or family financial
interests. Provide only such expert testimony as you would be content
to have peer reviewed.
B. Responsibilities to Funders, Clients,
and Employers
Where appropriate, present a client or employer with choices
among valid alternative statistical approaches that may vary in scope,
cost, or precision. Clearly state your statistical qualifications and
experience relevant to your work. Clarify the respective roles of different
participants in studies to be undertaken. Explain any expected adverse
consequences of failure to follow through on an agreed-upon sampling or
analytic plan. Apply statistical sampling and analysis procedures scientifically,
without predetermining the outcome. Make new statistical knowledge widely
available, in order to provide benefits to society at large beyond your
own scope of applications. Statistical methods may be broadly applicable
to many classes of problem or application. (Statistical innovators may
well be entitled to monetary or other rewards for their writings, software,
or research results.) Guard privileged information of the employer, client,
or funder. Fulfill all commitments. Accept full responsibility for your
professional performance.
C. Responsibilities in Publications
and Testimony
Maintain personal responsibility for all work bearing your name; avoid
undertaking work or coauthoring publications for which you would not want
to acknowledge responsibility. Conversely, accept (or insist upon) appropriate
authorship or acknowledgment for professional statistical contributions
to research and the resulting publications or testimony. Report statistical
and substantive assumptions made in the study. In publications or testimony,
identify who is responsible for the statistical work if it would not otherwise
be apparent. Make clear the basis for authorship order, if determined
on grounds other than intellectual contribution. Preferably, authorship
order in statistical publications should be by degree of intellectual
contribution to the study and to the material to be published, to the
extent that such ordering can feasibly be determined. When some other
rule of authorship order is used in a statistical publication, the rule
used should be disclosed in a footnote or endnote. (Where authorship order
by contribution is assumed by those making decisions about hiring, promotion,
or tenure, for example, failure to disclose an alternative rule may improperly
damage or advance careers.) Account for all data considered in a study
and explain the sample(s) actually used. Report the sources and assessed
adequacy of the data. Report the data cleaning and screening procedures
used, including any imputation. Clearly and fully report the steps taken
to guard validity. Address the suitability of the analytic methods and
their inherent assumptions relative to the circumstances of the specific
study. Identify the computer routines used to implement the analytic methods.
Where appropriate, address potential confounding variables not included
in the study. In publications or testimony, identify the ultimate financial
sponsor of the study, the stated purpose, and the intended use of the
study results. When reporting analyses of volunteer data or other data
not representative of a defined population, include appropriate disclaimers.
Report the limits of statistical inference of the study and possible sources
of error. For example, disclose any significant failure to follow through
fully on an agreed sampling or analytic plan and explain any resulting
adverse consequences. Share data used in published studies to aid peer
review and replication, but exercise due caution to protect proprietary
and confidential data, including all data which might inappropriately
reveal respondent identities. As appropriate, promptly and publicly correct
any errors discovered after publication. Write with consideration of the
intended audience. (For the general public, convey the scope, relevance,
and conclusions of a study without technical distractions. For the professional
literature, strive to answer the questions likely to occur to your peers.)
D. Responsibilities to Research Subjects
(including census or survey respondents and persons and organizations
supplying data from administrative records, as well as subjects of physically
or psychologically invasive research)
Know about and adhere to appropriate rules for the protection
of human subjects, including particularly vulnerable or other special
populations who may be subject to special risks or who may not be fully
able to protect their own interests. Assure adequate planning to support
the practical value of the research, the validity of expected results,
the ability to provide the protection promised, and consideration of all
other ethical issues involved. Some pertinent guidance is provided in
key references 3 - 7 at the end of this document for U.S. law, the U.N.
Statistical Commission, and the International Statistical Institute. Laws
of other countries and their subdivisions and ethical principles of other
professional organizations may provide other guidance. Avoid the use of
excessive or inadequate numbers of research subjects by making informed
recommendations for study size. These recommendations may be based on
prospective power analysis, the planned precision of the study endpoint(s),
or other methods to assure appropriate scope to either frequentist or
Bayesian approaches. Study scope should also take into consideration the
feasibility of obtaining research subjects and the value of the data elements
to be collected. Avoid excessive risk to research subjects and excessive
imposition on their time and privacy. Protect the privacy and confidentiality
of research subjects and data concerning them, whether obtained directly
from the subjects, from other persons, or from administrative records.
Anticipate secondary and indirect uses of the data when obtaining approvals
from research subjects; obtain approvals appropriate for peer review and
for independent replication of analyses. Be aware of legal limitations
on privacy and confidentiality assurances. Do not, for example, imply
protection of privacy and confidentiality from legal processes of discovery
unless explicitly authorized to do so. Before participating in a study
involving human beings or organizations, analyzing data from such a study,
or accepting resulting manuscripts for review, consider whether appropriate
research subject approvals were obtained. (This safeguard will lower your
risk of learning only after the fact that you have collaborated on an
unethical study.) Consider also what assurances of privacy and confidentiality
were given and abide by those assurances. Avoid or minimize the use of
deception. Where it is necessary and provides significant knowledge, as
in some psychological, sociological, and other research, assure prior
independent ethical review of the protocol and continued monitoring of
the research. Where full disclosure of study parameters to subjects or
to other investigators is not advisable, as in some randomized clinical
trials, generally inform them of the nature of the information withheld
and the reason for withholding it. As with deception, assure independent
ethical review of the protocol and continued monitoring of the research.
Know about and adhere to appropriate animal welfare guidelines in research
involving animals. Assure that a competent understanding of the subject
matter is combined with credible statistical validity.
E. Responsibilities to Research Team
Colleagues
Inform colleagues from other disciplines about relevant aspects of statistical
ethics. Promote effective and efficient use of statistics by the research
team. Respect the ethical obligations of members of other disciplines
as well as your own. Assure professional-quality reporting of the statistical
design and analysis. Avoid compromising statistical validity for expediency,
but use reasonable approximations as appropriate.
F. Responsibilities to Other Statisticians or Statistical
Practitioners
Promote sharing of (nonproprietary) data and methods. As appropriate,
make suitably documented data available for replicate analyses, metadata
studies, and other suitable research by qualified investigators. Be willing
to help strengthen the work of others through appropriate peer review.
When doing so, complete the review promptly and well. Assess methods,
not individuals. Respect differences of opinion. Instill in students a
positive appreciation for the practical value of the concepts and methods
they are learning. Use professional qualifications and the contributions
of the individual as an important basis for decisions regarding statistical
practitioners' hiring, firing, promotion, work assignments, publications
and presentations, candidacy for offices and awards, funding or approval
of research, and other professional matters. Avoid as best you can harassment
of or discrimination against statistical practitioners (or anyone else)
on professionally irrelevant bases such as race, color, ethnicity, sex,
sexual orientation, national origin, age, religion, nationality, or disability.
G. Responsibilities Regarding Allegations of Misconduct
Avoid condoning or appearing to condone careless, incompetent, or unethical
practices in statistical studies conducted in your working environment
or elsewhere. Deplore all types of professional misconduct, not just plagiarism
and data fabrication or falsification. Misconduct more broadly includes
all professional dishonesty, by commission or omission, and, within the
realm of professional activities and expression, all harmful disrespect
for people, unauthorized use of their intellectual and physical property,
and unjustified detraction from their reputations. Recognize that differences
of opinion and honest error do not constitute misconduct; they warrant
discussion but not accusation. Questionable scientific practices may or
may not constitute misconduct, depending on their nature and the definition
of misconduct used. If involved in a misconduct investigation, know and
follow prescribed procedures. Maintain confidentiality during an investigation,
but disclose the results honestly after the investigation has been completed.
Following a misconduct investigation, support the appropriate efforts
of the accused, the witnesses, and those reporting the possible scientific
error or misconduct to resume their careers in as normal a manner as possible.
Do not condone retaliation against or damage to the employability of those
who responsibly call attention to possible scientific error or misconduct.
H. Responsibilities of Employers,
Including Organizations, Individuals, Attorneys, or Other Clients Employing
Statistical Practitioners
Recognize that the results of valid statistical studies cannot be guaranteed
to conform to the expectations or desires of those commissioning the study
or the statistical practitioner(s). Any measures taken to assure a particular
outcome will lessen the validity of the analysis. Valid findings result
from competent work in a moral environment. Pressure on a statistical
practitioner to deviate from these guidelines is likely to damage both
the validity of study results and the professional credibility of the
practitioner. Make new statistical knowledge widely available in order
to benefit society at large. (Those who have funded the development of
new statistical innovations are entitled to monetary and other rewards
for their resulting products, software, or research results.) Support
sound statistical analysis and expose incompetent or corrupt statistical
practice. In cases of conflict, statistical practitioners and those employing
them are encouraged to resolve issues of ethical practice privately. If
private resolution is not possible, recognize that statistical practitioners
have an ethical obligation to expose incompetent or corrupt practice before
it can cause avoidable harm to research subjects or society at large.
Recognize that within organizations and within professions using statistical
methods generally, statistical practitioners with greater prestige, power,
or status have a responsibility to protect the professional freedom and
responsibility of more subordinate statistical practitioners to comply
with these guidelines. Do not include statistical practitioners in authorship
or acknowledge their contributions to projects or publications without
their explicit permission.
Key References:
1. American Statistical Association. Discussions of the statistics profession
and information about the organization are available on the Association's
home Web site: http://www.amstat.org 2. These ethical guidelines, case
studies in statistical ethics, and other related resources and links can
be found at the Ethics and Statistics Web site: http://www.tcnj.edu/~ethcstat
3. U.S. Federal regulations regarding human subjects protection are contained
in Title 45 of the Code of Federal Regulations, Chapter 46 (45 CFR 46),
accessible at: http://www.access.gpo.gov/cgi-bin/cfrassemble.cgi?title=199845,
using the search term "46." 4. The Belmont Report: Ethical Principles
and Guidelines for the Protection of Human Subjects of Research is available
through the Office for the Protection from Research Risks at: http://grants.nih.gov/grants/oprr/humansubjects/guidance/belmont.htm
5. Title 13, U.S. Code, Chapter 5 - Censuses, Subchapter II - Population,
housing, and unemployment, Sec. 141 restricts uses of U.S. population
census information. Similar restrictions may apply in other countries.
6. The International Statistical Institute's 1985 Declaration on Professional
Ethics is available at: http://www.cbs.nl/isi/ethics.htm 7. The United
Nations Statistical Commission's 1994 Fundamental Principles of Official
Statistics is available at: http://www.cbs.nl/isi/fundamental.htm --------------------------------------------------------------------------------
Members of the American Statistical Association (ASA) Committee on Professional
Ethics (1998-99): John Bailar, Paula Diehr, Susan Ellenberg, John Gardenier
(Chair), Lilliam Kingsbury, David Levy, Lisa McShane, Richard Potthoff,
Jerome Sacks, Juliet Shaffer, and Chamont Wang. Other contributing advisors
in the preparation of these guidelines: Martin David, Virginia deWolf,
Mark Frankel (American Association for the Advancement of Science), Joseph
Kadane, Mary Grace Kovar, Michael O'Fallon, Fritz Scheuren, and William
Seltzer. Helpful reviews of these guidelines were provided by the Council
of Sections, Beth Dawson, Chair, and by the Council of Chapters, Brenda
Cox, Chair. Thanks to many persons who commented on successive drafts
or participated in discussions of the Guidelines at the 1998 Joint Statistical
Meetings, Dallas, Texas. We also thank the various ASA Boards and the
ASA Presidents who have supported this effort, especially Lynne Billard,
Jon Kettenring, David Moore, and Jonas Ellenberg, as well as ASA Executive
Director, Ray Waller.
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